Driving Innovation by Dynamic Optimization : The Challenges of Reshaping Industry

Future-proof your technical expertise by mastering the multidisciplinary synergy of AI-driven optimization and intelligent algorithms with this essential resource to optimization for the modern world.

The rapid evolution of artificial intelligence, machine learning, and data-driven optimization has transformed the landscape of scientific research and industrial innovation. This book presents a diverse and multidisciplinary collection of contemporary studies that advance theoretical foundations, computational techniques, and application-driven solutions across multiple domains to reflect the growing importance of optimization, intelligent systems, and hybrid analytical frameworks in solving complex real-world problems. This essential guide focuses on next-generation technologies such as AI-driven cybersecurity, dynamic optimization in 6G networks, fuzzy logic-based energy management, automated neural machine translation, and GAN-driven aerodynamic shape design, illustrating the synergy between intelligent algorithms and modern engineering systems. Whether you are a researcher, practitioner, or simply an enthusiast, this book will serve as an enlightening resource, providing valuable insights into the ever-evolving realm of optimization for the modern world.

Readers will find the volume:

• Provides comprehensive coverage of the backgrounds, foundations, and theoretical ideas of optimization methods and their potential applications;
• Introduces applications of fuzzy sets for solving optimization problems in real-life scenarios;
• Explores the transformative potential of fuzzy sets for optimization across several domains like healthcare, finance, and education.

Audience

Researchers, academics, industry experts, scientists, and technologists looking for insights into advances across optimization theory, machine learning, deep learning, cybersecurity, healthcare analytics, energy systems, and intelligent decision-making.

Arindam Dey, PhD is an Associate Professor in the School of Computer Science at the Vellore Institute of Technology, Tamil Nadu, India, with more than 14 years of teaching and research experience. He has published more than 50 research articles in national and international peer-reviewed journals. His research focuses on fuzzy optimization and genetic algorithms.

Sachi Nandan Mohanty, PhD is a Professor in the School of Computer Science and Engineering at the Vellore Institute of Technology, Tamil Nadu, India. He has authored and edited 42 books and published more than 120 articles in international journals of repute. His research interests include data mining, big data analysis, cognitive science, fuzzy decision-making, brain-computer interface, cognition, and computational intelligence.

Ranjan Kumar, PhD is an Assistant Professor at MLSM College, Darbhanga, Bihar, India, with more than ten years of experience in research, teaching, and industry. He is a reputed academician with significant contributions as a reviewer, associate editor, book editor, and editorial board member for internationally acclaimed research journals. His research in mathematics focuses on fuzzy optimization.

T. Rajasanthosh Kumar, PhD is an Associate Professor at Puducherry Technological University, Puducherry, India. He has published 35 articles in internationals journals and conferences and two textbooks and has 25 granted patents to his credit. His research focuses on mechanical design and manufacturing.